extractProtPSSMAcc {Rcpi} | R Documentation

## Profile-based protein representation derived by PSSM (Position-Specific Scoring Matrix) and auto cross covariance

### Description

Profile-based protein representation derived by PSSM (Position-Specific Scoring Matrix) and auto cross covariance

### Usage

    extractProtPSSMAcc(pssmmat, lag)

### Arguments

`pssmmat` | The PSSM computed by `extractProtPSSM`.
`lag` | The lag parameter. Must be less than the number of amino acids in the sequence (i.e. the number of columns in the PSSM matrix).

### Details

This function calculates the feature vector based on the PSSM by running PSI-Blast and auto cross covariance tranformation.

### Value

A length `lag * 20^2` named numeric vector, the element names are derived by the amino acid name abbreviation (crossed amino acid name abbreviation) and lag index.

### Author(s)

Nan Xiao <https://nanx.me>

### References

Wold, S., Jonsson, J., Sj\"orstr\"om, M., Sandberg, M., & R\"annar, S. (1993). DNA and peptide sequences and chemical processes multivariately modelled by principal component analysis and partial least-squares projections to latent structures. Analytica chimica acta, 277(2), 239–253.

### See Also

extractProtPSSM extractProtPSSMFeature

### Examples

    x = readFASTA(system.file('protseq/P00750.fasta', package = 'Rcpi'))[[1]]

    dbpath = tempfile('tempdb', fileext = '.fasta')
    invisible(file.copy(from = system.file('protseq/Plasminogen.fasta', package = 'Rcpi'), to = dbpath))
    pssmmat = extractProtPSSM(seq = x, database.path = dbpath)
    pssmacc = extractProtPSSMAcc(pssmmat, lag = 3)
    tail(pssmacc)

[Package Rcpi version 1.26.0 Index]